Hybrid filtering-based personalized recommender system for revitalization of Jeju water industry

Authors:
Jungwon Cho;Eui-young Kang;Hanil Kim;Hyungchul Kim;Youngseok Lee;Seungdo Jeong
Affiliations:
Dept. of Computer Education, Jeju National University, Jeju-si, Jeju-do, S. Korea;Dept. of Computer Education, Jeju National University, Jeju-si, Jeju-do, S. Korea;Dept. of Computer Education, Jeju National University, Jeju-si, Jeju-do, S. Korea;Dept. of Computer Education, Jeju National University, Jeju-si, Jeju-do, S. Korea;Dept. of Electronics Computer Engineering, Hanyang University, Seoul, S. Korea;Dept. of Information & Communication Engineering, Hanyang Cyber University, Seoul, S. Korea
Venue:
ICWL'10 Proceedings of the 2010 international conference on New horizons in web-based learning
Year:
2010

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Abstract

Information filtering is one of the core technologies in a recommender system for personalized services. Each filtering technology has such shortcomings as new user problems and sparsity. Moreover, a recommender system dependent on items decreases reusability. In order to solve these problems, we developed a personalized recommender framework with hybrid filtering. This framework consists of reusable and flexible modules for recommended items. Further, this framework improves the productivity of programming. As an application of this framework, we implemented a personalized tourist recommender system and analyzed it. Also, we applied the system to Jeju beer recommender system. The results show the performance of the framework proposed in this paper.